Dear Data Method Community,
Communication has never been easy, but is very key in any collaboration be it long or short term.
In medicine we are taught ways to communicate with patients. But communication is a two way event, and unfortunately patients are not taught how to communicate with doctors, so in the course of a doctors practice, they learn the art of decoding what the patient might be trying to say. At times one can verify some diagnosis hypothesis with medical tests, or look for signs and symptoms that are independent of the patient’s ability to articulate what they think is wrong with them. You get the point. All this is largely because clinicians and patients don’t share a common set of vocabulary and/or thanks to google, a common understanding of medical vocabulary - you have all probably heard of the phenomenon where patients google their symptoms until they self-diagnose, and at times hilariously they reduce a clinicians role to one of writing their prescription for they will have also googled which drug to take. Then the clinicians role expands to de-diagnosing (if the patient got it wrong) the patient, before properly diagnosing them.
Similarly, statisticians and (most, I included) non-statisticians don’t share a common set of vocabulary, or at times the understanding of the same vocabulary, so I can imagine, that the “Statistician - non-statistician communication” within a collaboration is not easy either. A non-statistician might approach a statistician with a “simple” question which later turns out to be not-so-simple after discussion, or a statistician gives suggestions which are later implemented in ways that make it obvious (to the statistician at least) that he/she was clearly completely misunderstood.
Thus am interested to learn about:
As a statistician, what has been your experience?
As a non-statistician, what has been your experience?
From your experience, what have you done (or are some of the ways) to improve this communication?